Smoke root detection from video sequences based on multi-feature fusion
Author:
Publisher
Springer Science and Business Media LLC
Subject
Forestry
Link
https://link.springer.com/content/pdf/10.1007/s11676-022-01461-w.pdf
Reference29 articles.
1. Alamgir N, Nguyen K, Chandran V, Boles W (2018) Combining multichannel color space with local binary co-occurrence feature descriptors for accurate smoke detection from surveillance videos. Fire Saf J 102:1–10. https://doi.org/10.1016/j.firesaf.2018.09.003
2. Appana DK, Islam R, Khan SA, Kim JM (2017) A video-based smoke detection using smoke flow pattern and spatial-temporal energy analyses for alarm systems. Inf Sci 418–419:91–101. https://doi.org/10.1016/j.ins.2017.08.001
3. Barmpoutis P, Dimitropoulos K, Grammalidis N (2013) Real time video fire detection using spatio-temporal consistency energy. IEEE AVSS 2013. https://doi.org/10.1109/AVSS.2013.6636667
4. Cheng SH, Ma JY, Zhang SJ (2019) Smoke detection and trend prediction method based on deeplabv3+ and generative adversarial network. J Electron Imaging 28:033006–033006. https://doi.org/10.1117/1.JEI.28.3.033006
5. Gao Y, Cheng PL (2021) Full-scale video-based detection of smoke from forest fires combining ViBe and MSER algorithms. Fire Technol. https://doi.org/10.1007/s10694-020-01052-3
Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Lightweight wildfire smoke monitoring algorithm based on unmanned aerial vehicle vision;Signal, Image and Video Processing;2024-06-28
2. UAV-FDN: Forest-fire detection network for unmanned aerial vehicle perspective;Journal of Intelligent & Fuzzy Systems;2023-10-04
3. Fully Automatic Approach for Smoke Tracking Based on Deep Image Quality Enhancement and Adaptive Level Set Model;Electronics;2023-09-14
4. Wildfire Detection via a Dual-Channel CNN with Multi-Level Feature Fusion;Forests;2023-07-21
5. Hybrid Feature Fusion-Based High-Sensitivity Fire Detection and Early Warning for Intelligent Building Systems;Sensors;2023-01-11
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3